Examining Hidden Meaning of E-commerce Platform
Rajesh Bose1, Raktim Kumar Dey2, Srabanti Chakraborty3, Sandip Roy4, Debabrata Sarddar5

1Dr. Rajesh Bose, Simplex Infrastructures Limited, Kolkata, India.
2Raktim Kumar Dey, Simplex Infrastructures Limited, Mumbai, India.
3Srabanti Chakraborty, Dept. of CST, EIEM, Kolkata, India.
4Dr. Sandip Roy*, Dept. of CSE, Brainware University, Kolkata, India.
5Dr. Debabrata Sarddar, Dept. of CSE, University of Kalyani, Kalyani, India. 

Manuscript received on September 17, 2019. | Revised Manuscript received on 24 September, 2019. | Manuscript published on October 10, 2019. | PP: 257-261 | Volume-8 Issue-12, October 2019. | Retrieval Number: L36481081219/2019©BEIESP | DOI: 10.35940/ijitee.L3648.1081219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Different e-commerce companies try to maintain high importance for their customer satisfactions. It helps them to understand the performance of their products. Nowadays customers trust on the product reviews while shipping online. But it is a cumbersome task to handle millions of customer reviews within specific time period. Due to this problem consumers usually follow the set of reviews before taking decision for purchasing any products from online. Although, each consumer rates the product from 1 to 5 stars, these overall product rating judge products towards their customers satisfaction. Consumers also provide a text based summary as a review of their experiences and opinions about the products. Customer sentiment analysis is a method to process these customer reviews to summarize different products. In this manuscript, we analyzed the text summery of Amazon food products using NRC Emotion Lexicon to determine the overall responses of the products using eight emotions of the customers. Our result can be used to take further decision making for the future of the products.
Keywords:  Amazon Customer Reviews, Latent Dirichlet Allocation (LDA), Opinion mining, Sentiment Analysis, Topic Modeling, Word Cloud.
Scope of the Article: E-commerce